1. Field of the Invention
The present invention relates to radar systems and associated methods. More specifically, the present invention relates to systems and methods for improving radar image quality.
2. Description of the Related Art
Synthetic Aperture Radar (SAR) uses a side looking radar aperture on a moving platform to provide high-resolution imagery over a broad area. The concept usually employs airborne radar that collects data while flying some distance, and then processes the data coherently as if it came from a physically long antenna (See Introduction to Airborne Radar by G. W. Stimson, published 1998 by Scitech Pub Inc, pp. 527-549.)
This synthetically long antenna aperture provides superior image resolution over that of the actual antenna and overcomes the weather dependent nature of all optical remote-sensing systems. While the ability of SAR radars to produce better and better imagery advances, the ability of those same radars to autonomously distinguish stationary ground vehicles from background clutter remains difficult.
Template based methods use previously collected images from known vehicles to identify targets within a scene. (See “The Automatic Target-Recognition System in SAIP”, by L. M. Novak, et al., Lincoln Laboratory Journal, vol. 10, no. 2, pp 187-203, 1997 and “An efficient multi-target SAR ATR Algorithm”, by L. M. Novak, et al., published by the Massachusetts Institute of Technology/Lincoln Laboratory, Lexington, Mass.)
The process of template based target identification begins with a simple localized constant false alarm rate (CFAR) detection test to remove any objects that are not locally bright, then a discrimination layer is applied that removes any non-target like objects. These two layers of processing are performed before the template processing is applied, since the template based processing can be easily overwhelmed with a high false alarm rate.
Another problem of template based target identification is that its performance is based on prior knowledge of the target. The total number of different target types that need to be identified also affects performance. One drawback of template based target detection methods is that small variations in target configurations can reduce the effectiveness of the templates.
Also, since a SAR image contains many small scatters whose physical size is on the order of the radar's wavelength, constructive and destructive interference of the complex returns produces phenomena called speckle, which reduces image quality and decreases probability of target detection. Smoothing and spatial filtering techniques can reduce speckle and help increase the probability of detection. (See “Application of angular correlation function of clutter scattering and correlation imaging in target detection”, by G. Zhang, L. Tsang, IEEE Transactions on Geoscience and Remote Sensing, Volume 36, Issue 5, Part 1, pp. 1485-1493, September 1998.) However, these approaches remain inadequate for current more demanding applications.
Hence, a need remains in the art for an improved radar system or method for imaging a target that addresses problems associated with speckle.